How to Make Data Analysis Ten Times Faster with AI and Large Language Models
The DataOps Way to Data Quality: A Free Book for Every Data Team
Most data quality advice tells you what to measure. This book tells you why your team keeps failing and what to actually do about it.
Why Your Data Quality Dashboard Isn’t Working And What to Do About It
This article pulls back the curtain on why standard data quality dashboards fall short. We’ll reveal six powerful, and perhaps surprising, truths about data quality dashboard failure.
We Got Roasted On Reddit For Asking ‘Why Data Engineers Don’t Test?’
We asked the r/dataengineering community ‘Why don’t you test?’ And we got roasted. Learn why
Be The First To Know: Smart, Continuous Table Monitoring Has Arrived In TestGen
The days of learning about data problems from an angry business analyst should be over. With TestGen’s table monitoring, you’re watching everything automatically and continuously.
Data Quality Testing Is At The Core of Four Critical Data Team Processes
What Is The Common Thread Running Through Four Critical Data Team Processes? Data Testing!
Stop Paying The Data Quality Tax
Why Data Observability costs a fortune, why it shouldn’t, and why paying $100,000/year for commodity algorithms is insane!
Data Quality vs. Data Observability: The Pets and Cattle of Your Data Estate
The same “pets vs cattle” philosophy that transformed Devops explains exactly when to invest in data quality dashboards versus when to rely on automated anomaly detection—and why you need both.
How TestGen Complements Microsoft Purview for Enterprise Data Quality
DataKitchen’s TestGen and Microsoft’s Purview complement each other: Purview serves as the governance and catalog “source of truth,” while TestGen is the deep, automated data-quality and testing engine that writes thousands of data quality tests in seconds.
The Five Organizational Sins of Data Teams
The five organizational problems are systemic failures of culture and structure that lead to warring teams, a corrosive blame culture, “data blindness” regarding pipelines, a short-term project mindset, and the chaotic scattering of business logic. Learn how to identify and fix below.
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The Equation For AI Success: DT + DX + CTX = 10xMarch 10, 2026
